Gerald Lip
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- IgG4-Related and Inflammatory Diseases
Papers in
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- Artificial Intelligence in Healthcare and Education 7
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- Radiomics and Machine Learning in Medical Imaging 6
- Radiology practices and education 2
- Co-authors
- Zhongxiang Ding (2 shared papers)Vincent F Chong (1 shared paper)Roger T. Staff (4 shared papers)Nichols Dm (1 shared paper)Lisa Iversen (1 shared paper)Lesley Ann Anderson (5 shared papers)Valerie Speirs (2 shared papers)Peter Murchie (1 shared paper)
- Journals
- Clinical Radiology (4 papers)Adipocyte (1 paper)BMC Health Services Research (1 paper)Nature Cancer (1 paper)Psychology Health & Medicine (1 paper)
- Partner nations
- United KingdomSingaporeChina
In The Last Decade
Gerald Lip
27 papers receiving 272 citations
Peers
Comparison fields: 5 of 55
- Health Informatics 57
- Rheumatology 48
- Ophthalmology 22
- Radiology, Nuclear Medicine and Imaging 52
- Otorhinolaryngology 6
Countries citing papers authored by Gerald Lip
This map shows the geographic impact of Gerald Lip's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gerald Lip with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gerald Lip more than expected).
Fields of papers citing papers by Gerald Lip
This network shows the impact of papers produced by Gerald Lip. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gerald Lip. The network helps show where Gerald Lip may publish in the future.
Co-authors
The 25 scholars most cited alongside Gerald Lip, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 58 | |
| 2 | 2023 | 40 | |
| 3 | 2017 | 24 | |
| 4 | 2021 | 20 | |
| 5 | 2023 | 18 | |
| 6 | 2022 | 18 | |
| 7 | 2024 | 16 | |
| 8 | 2013 | 15 | |
| 9 | 2021 | 14 | |
| 10 | 2010 | 9 | |
| 11 | 2002 | 8 | |
| 12 | 2009 | 7 | |
| 13 | 2024 | 6 | |
| 14 | 2024 | 4 | |
| 15 | 2018 | 3 | |
| 16 | 2024 | 3 | |
| 17 | 2012 | 2 | |
| 18 | 2024 | 2 | |
| 19 | Teaching Anatomy Using Multimedia | 2000 | 2 |
| 20 | 2023 | 2 |
About Gerald Lip
Gerald Lip is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Oncology and Cancer Research, having authored 28 papers that have together received 279 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (7 papers), AI in cancer detection (7 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Global Cancer Incidence and Screening (4 papers), Digital Radiography and Breast Imaging (2 papers), Radiology practices and education (2 papers), Breast Cancer Treatment Studies (2 papers) and IgG4-Related and Inflammatory Diseases (2 papers). The work is most often cited by research in Health Informatics (57 citations), Rheumatology (48 citations), Ophthalmology (22 citations), Radiology, Nuclear Medicine and Imaging (52 citations) and Otorhinolaryngology (6 citations). Gerald Lip has collaborated with scholars based in United Kingdom, Singapore and China. Frequent co-authors include Zhongxiang Ding, Vincent F Chong, Roger T. Staff, Nichols Dm, Lisa Iversen, Lesley Ann Anderson, Valerie Speirs, Peter Murchie, Nathan Chan and Antonia C. Lyons. Their work appears in journals such as Clinical Radiology, Adipocyte, BMC Health Services Research, Nature Cancer and Psychology Health & Medicine.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.